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Characterizing the Complex Permittivity of an Isotropic Scatterer in a Homogeneous Environment Using an Open-Ended Coaxial Probe

2024· article· en· W4402968219 on OpenAlexaff
Rotem Gal-Katzir, Emily Porter, Yarden Mazor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsIsotropyPermittivityHomogeneousCoaxialMaterials scienceRelative permittivityAcousticsOpticsPhysicsDielectricMechanical engineeringEngineeringOptoelectronicsThermodynamics

Abstract

fetched live from OpenAlex

Electromagnetic-based biomedical technologies often depend on accurately estimating tissues' dielectric properties. The open-ended coaxial probe (OECP) technique is one of the simplest and most commonly used methods to obtain the complex permittivity of tissues over the radio or microwave frequency ranges. However, when considering diseased tissues, we encounter tissue heterogeneities, which alter the measured parameters. To quantify this effect, we focus on characterizing an isotropic scatterer within an otherwise homogeneous medium using OECPs. We present an analytical model relating the reflection coefficient to the scatterer properties and derive a closed-form expression for the effective measured admittance. Based on full-wave simulations, we demonstrate that our theoretical model provides accurate estimates of the scatterer permittivity. We use the analytical model to characterize the sensing depth of different OECP systems, providing a performance guideline.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.274
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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